AI-enabled Analysis of Our Social Expression and Interactions in Digital Age

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https://kaust.zoom.us/j/96464686903

Abstract

Half of the total global population are using social media and produce a huge amount of user-generated content and interaction records on Facebook, Twitter, Instagram, YouTube, LinkedIn and so on. AI and machine learning techniques have been leveraged to understand the unprompted feelings, opinions and preference of users by analyzing their social expression and interactions. This talk will introduce the advantages brought by the AI-powered recommendation systems, from which we have benefited to have an easy discovery of the posts we like to see on our favorite social networks, the useful products to purchase online, the interesting places to visit, etc. The key is to understand users’ interests and needs by learning from their historically generated content and interactions. The talk will also introduce our study of sentiment variation during the outbreak of Covid-19 for knowing how people feel in pandemic. The results are from deep learning language processing models applied on 105+ million tweets and Weibo messages in six different languages on COVID-19 (covering English, Spanish, French, Italian, Arabic and Chinese).
 

Brief Biography

Dr. Xiangliang Zhang is an Associate Professor of Computer Science and directs the MINE (http://mine.kaust.edu.sa) group at KAUST, Saudi Arabia. She earned her Ph.D. degree in computer science from INRIA-University Paris-Sud, France, in July 2010. She received her M.S. and B.S. degrees from Xi’an Jiaotong University, China, in 2006 and 2003, respectively. Dr. Zhang's research mainly focuses on learning from complex and large-scale streaming data and graph data, with applications on recommendation systems, biomedical knowledge discovery and social media data analysis. Dr. Zhang has published over 160 research papers in referred international journals and conference proceedings, including TKDE, SIGKDD, AAAI, IJCAI, NeurIPS, ICDM, etc.   She regularly serves on the Program Committee for premier conferences like SIGKDD (Senior PC), AAAI (Senior PC), IJCAI (Area Chair, Senior PC), ICDM, NIPS, ICML etc.  Dr. Zhang was invited to deliver an Early Career Spotlight talk at IJCAI-ECAI 2018.

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